Clustered panel data models: an efficient approach for nowcasting from poor data

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• 作者：Mouchart ; Michel ; Rombouts ; Jeroen V.K.
• 关键词：Panel data ; Forecast ; Nowcast ; Missing data ; Clustering ; R& ; D data
• 刊名：International Journal of Forecasting
• 出版年：2005
• 出版时间：July - May, 2005
• 年：2005
• 卷：21
• 期：3
• 页码：577-594
• 全文大小：223 K

文摘

Nowcasting concerns the inference on the current realization of random variables using information available until a recent past. This paper proposes a modelling strategy aimed at the best use of data for nowcasting based on panel data with severe deficiencies, namely, short time series and many missing data. The basic idea consists of introducing a clustering approach into the usual panel data model specification. A case study in the field of R&D variables illustrates the proposed modelling strategy.